Item: Google Cloud Run
Rating: 10
Author: Harold Snyers

Overall Satisfaction with Google Cloud Run

Use Cases and Deployment Scope

In our organization we use Google Cloud Run, and now Cloud Run functions, for all kinds of applications. We use it as microservices for API applications, we use it to deploy GenAI application running with Langchain, and all kinds of other stuff. The big advantage of Cloud Run is that it is almost self managed, we only it to create our Docker container, and specify some configuration about memory, cpu, and instances, and all the rest is managed by Google. Rarely or never had problems with Cloud Run itself.

Pros and Cons

Pros

Manage number of instances given the rate request
easily deployable
infrastructure as code in terraform available
fast and reliable
Supports different languages seamlessly

Cons

Missing, like in cloud function, an interface for easy testing
feature for automatic dashboards based on requests for API like applications

Return on Investment

Cost saving, as you can scale down to zero or 1
Increase in productivity because you don't need to worry about infrastructure
Secure and consistent for accessing the service

Alternatives Considered

Google Cloud Dataflow, Google Cloud Functions and Google Compute Engine

Key Insights

Do you think Google Cloud Run delivers good value for the price?

Yes

Are you happy with Google Cloud Run's feature set?

Yes

Did Google Cloud Run live up to sales and marketing promises?

Yes

Did implementation of Google Cloud Run go as expected?

Yes

Would you buy Google Cloud Run again?

Yes

Other Software Used

Google BigQuery, Vertex AI, Google Cloud Datastore, Google Cloud Dataflow, Dataform, dbt, Fivetran, Airbyte, LangChain, Gemini

Likelihood to Recommend

Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

Google Cloud Run Feature Ratings

Comments

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Effortless Deployment with Google Cloud Run